Comments (1)
@xsurkan in order to resume training from a loaded checkpoint you can use:
checkpoint_handler = CheckpointHandler()
checkpoint_handler = checkpoint_handler.load_checkpoint(checkpoint_path)
model = Net()
model.load_state_dict(checkpoint_handler.model_state_dict)
model = model.to(device)
optimizer = optim.SGD(model.parameters(), lr=args.lr, momentum=args.momentum)
optimizer.load_state_dict(checkpoint_handler.optimizer_state_dict)
Now you can continue training using your code. Notice that you can resume from a specific epoch, in your code you set iteration=2
this needs to be epoch
from pytorch-checkpoint.
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from pytorch-checkpoint.